PPT An Introduction to Behavioral Finance PowerPoint presentation
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An Introduction to Behavioral Finance
An Introduction to Behavioral Finance SIP Course on Stock Market Anomalies and Asset Management Professors S.P. Kothari and Jon Lewellen March 15, 2004 PowerPoint PPT presentation
Title: An Introduction to Behavioral Finance
An Introduction to Behavioral Finance
- SIP Course on Stock Market Anomalies and Asset
Management
An Introduction to Behavioral Finance
- Efficient markets hypothesis
- Large number of market participants
- Incentives to gather and process information
analysis until individual participants valuation
is similar to the observed market price
available to the participants, which means
opportunities to earn above-normal rates of
return on a consistent basis are limited
to predict
higher rates of returns compared to less risky
firms
An Introduction to Behavioral Finance
- Behavioral finance
- Widespread evidence of anomalies is inconsistent
with the efficient markets theory
theory of markets
events
IPOs, dividend initiations, seasoned equity
issues, earnings announcements, accounting
accruals
overreaction, medium-term momentum, and long-run
overreaction
An Introduction to Behavioral Finance
- Behavioral finance theory rests on the following
three assumptions/characteristics
that cause them to over- and under-react
information must be correlated across investors
so that they are not averaged out
investors should not be sufficient to make
markets efficient
Behavioral finance theories
- Human information processing biases
- Information processing biases are generally
relative to the Bayes rule for updating our
priors on the basis of new information
theories
1982)
self-attribution
Behavioral finance theories
- Human information processing biases
- Representativeness bias causes people to
over-weight recent information and deemphasize
base rates or priors
found on the street is gold (i.e. ignore the low
base rate of finding gold)
underlying distribution on the basis of sample
information
recent high sales growth and thus overreact to
news in sales growth
behavioral finance models of market inefficiency
Behavioral finance theories
- Human information processing biases
- Conservatism bias Investors are slow to update
their beliefs, i.e. they underweight sample
information which contributes to investor
under-reaction to news
to new information
tendency of stock prices to drift in the
direction of earnings news for three-to-twelve
months following an earnings announcement also
entails investor under-reaction
Behavioral finance theories
- Human information processing biases
- Investor overconfidence
- Overconfident investors place too much faith in
their ability to process information
about the companys prospects
investors private information
investors private information
Behavioral finance theories
- Human information processing biases
- Investor overconfidence and biased
self-attribution
self-attribution together result in a continuing
overreaction that induces momentum.
the investor overconfidence, however, resulting
in predictable price reversals over long
horizons.
down play the importance of some publicly
disseminated information, information releases
like earnings announcements generate incomplete
price adjustments.
Behavioral finance theories
- In addition to exhibiting information-processing
biases, the biases must be correlated across
investors so that they are not averaged out
evolutionary past
systematic biases among people
Behavioral finance theories
- Limited arbitrage
- Efficient markets theory is predicated on the
assumption that market participants with
incentives to gather, process, and trade on
information will arbitrage away systematic
mispricing of securities caused by investors
information processing biases
return on their information-gathering activities
arbitrage forces are constantly at work
there is mispricing, i.e. mispricing exists in
equilibrium
Behavioral finance theories
- Behavioral finance assumes arbitrage is limited.
What would cause limited arbitrage?
there is mispricing
sufficient
persist for long periods because arbitrage is
costly
impact/slippage
of short selling
analysis and monitoring
Behavioral finance theories
- Why cant large firms end limited arbitrage?
- Arbitrage requires gathering of information about
a firms prospects, spotting of mispriced
securities, and trading in the securities until
the mispricing is eliminated
have the capital needed for trading
must also delegate decision making (i.e.
trading) authority to those who possess the
information (agents)
principal, so decisions must be made by those who
possess information
but the principal sets limits on the amount of
capital at the agents disposal (the book)
Behavioral finance theories
- Like the efficient markets theory, behavioral
finance makes predictions about pricing behavior
that must be tested
adequate descriptor of the stock market behavior
as the anomalies literature documents
inconsistencies with the efficient markets
hypothesis
Stock Returns, Aggregate Earnings Surprises, and
Behavioral Finance
S.P. Kothari, Jonathan Lewellen, Jerold B.
Warner SIP Course on Stock Market Anomalies
and Asset Management March 15, 2004
Objective of the study
- We study the relation between market index
returns and aggregate earnings surprises
earnings changes?
Motivation
- At the firm level, post-earnings announcement
drift is well-known
inconsistent with market efficiency
finance
out-of-sample test of the behavioral hypothesis
of investor underreaction
predictability
Main findings
- Aggregate relation does not mimic the firm-level
relation
surprises
related to concurrent earnings news
positively correlated
eliminate the negative correlation between
earnings news and returns, a troubling result
Firm level drift and behavioral models
- Drift could occur if investors systematically
ignore the time-series properties of earnings.
earnings changes have positive serial dependence
(.34,.19,.06 at the first 3 lags)
will respond slowly and they will be surprised by
predictable changes in earnings.
profits at subsequent earnings announcements
matches the autocorrelation pattern.
Evidence
- Time-series properties of earnings
- Stock returns and aggregate earnings surprises
- Returns, earnings, and discount rates
Earnings series
- Compustat Quarterly database, 1970 2000
- NYSE, Amex, and NASDAQ stocks with
- Earnings before ext. items, quarter t and t 4
- Price, quarter t 4
- Book value, quarter t 4
- Plus
- December fiscal year end
- Price gt 1
- Exclude top and bottom 0.5 based on dE/P
